Optimizing mechanical properties of spark plasma sintered ZTA using neural network and genetic algorithm

This study involves optimizing hardness and toughness of spark plasma sintered ZTA through modeling followed by experimental validation. The simulated and experimentally observed results were in close agreement to each other. The parametric order of ‘importance’ for optimization was zirconia content, SPS temperature and heating rate.

► Spark plasma sintering of ZTA carried out at different conditions.
► Mechanical properties of ZTA optimized using neural network and genetic algorithm.
► Optimized conditions obtained at T: 1545 K, heat rate: 600 K min−1, ZrO2 content: 9 wt%.
► Distribution of zirconia in alumina is best at 9 wt% zirconia content.
► The parametric order of importance: zirconia content, SPS temperature and heat rate.